Quantitative determination of microbial materials activity based on infrared extinction properties

Area of Science:

• Microbiology
• Spectroscopy
• Biophysics

Background:

• Microbial activity is crucial for natural and human systems.
• Accurate determination of microbial activity is essential but challenging.
• Existing methods may lack speed or precision.

Purpose of the Study:

• To develop a quantitative method for determining microbial activity.
• To utilize infrared spectroscopy and extinction properties for this purpose.
• To establish predictive models for microbial activity.

Main Methods:

• Calculating complex refractive indices from infrared spectra.
• Determining extinction properties using discrete dipole approximation.
• Building quantitative models with partial least squares (PLS), support vector regression (SVR), and extreme learning machine (ELM).
• Employing least angle regression (LAR) combined with PLS for optimal prediction.

Main Results:

• Models were successfully established to predict microbial activity based on infrared extinction properties.
• The optimal model (LAR + PLS) demonstrated high predictive accuracy.
• Coefficients of determination (R²) reached up to 0.9744 for tested biomaterials.

Conclusions:

• Infrared extinction properties provide a viable basis for quantitative microbial activity determination.
• The developed method offers a rapid and accurate approach for assessing microbial activity.
• This technique has significant potential for various applications requiring microbial monitoring.